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+--- Thread: vision-language models on consumer gear with llama.cpp (/showthread.php?tid=1245)
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Re: vision-language models on consumer gear with llama.cpp - rocmhouse90 - 10-19-2026
Quote:What worked for me was pretty simple. If you're on MLX, I'd confirm the version first and then reduce variables until the behavior is obvious.
Interesting, I hadn't tried that. I don't think your conclusion is far off. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing.
Re: vision-language models on consumer gear with llama.cpp - cachelab - 10-19-2026
I'd approach it in a boring order. Before rebuilding anything, I'd test one clean baseline with Mixtral and compare from there.
Re: vision-language models on consumer gear with llama.cpp - visionforge - 10-19-2026
My first guess would be this: Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at NVFP4. Once you know the plain path works, then add the faster path back in piece by piece.